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Haze removal has been a very challenging problem due to its ill-posedness,which is more ill-posed if the input data is only a single hazy image. In thispaper, we present a new approach for removing haze from a single input image.The proposed method combines the model widely used to describe the formation ofa haze image with the assumption in Retinex that an image is the product of theillumination and the reflection. We assume that the depth and reflectionfunctions are spatially piecewise smooth in the model, where the totalvariation is used for the regularization. The proposed model is defined as aconstrained optimization problem, which is solved by an alternatingminimization scheme and the fast gradient projection algorithm. Some theoreticanalyses are given for the proposed model and algorithm. Finally, numericalexamples are presented to demonstrate that our method can restore vivid andcontrastive hazy images effectively.

Depth and Reflection Total Variation for Single Image Dehazing